Health behavior is the single greatest determinant of health. We want people to take their medication as prescribed, follow healthful diets, get adequate sleep, and avoid harmful substances and addictions. These actions may be thought of as binary behaviors-adherence and abstinence-that individuals may engage in-or not-on a daily basis. Yet, clinical trials of substance use treatment or abstinence use widely disparate measures of effect. There is no obvious biological or behavioral explanation for these disparate measurements. Further, measures of adherence and abstinence often fail to account for the rich variation in the pattern of the health behavior. These patterns of adherence or abstinence may further contribute to the individual's prognosis. This proposal offers a novel method to measure adherence and abstinence, using concepts adapted from network analysis. The gamma index, which measures the connectedness of doses taken (or substances not taken), accounts for the pattern of an individual's adherence, or abstinence, in an innovative algebraic model. This index can be used to model adherence and abstinence to examine their effect on clinically relevant biologic outcomes. Gamma is bounded at a value of 0 for perfect non-adherence (or non-abstinence), and 1 for perfect adherence (or perfect abstinence). We propose to analyze a series of datasets from completed clinical trials in four domains (1) adherence to Highly Active Antiretroviral Therapy (HAART) in subjects with HIV/AIDS; (2) adherence to buprenorphine treatment in subjects with opioid dependence; (3) abstinence from tobacco in trials of smoking cessation; and (4) abstinence or reduction in drinking in trials of subjects with alcohol use disorders. In trials of antiviral adherence, we will examine associations between the index and changes in viral load. In trials of tobacco, alcohol and drug treatment, we will examine associations between the index and long-term abstinence rates. The Specific Aims of this project are to (1) Assess the ability of the gamma index to improve the explanatory power of adherence on changes in viral load in trials of antiviral therapy in individuals infected with HIV, and (2) Assess the ability of the gamma index to explain differences in cessation endpoints in trials of subjects with substance use disorders, such as alcohol abuse, drug use, and smoking. Daily records of adherence (or substance use) are needed for this modeling, which makes these studies, which employ ecological momentary assessment (EMA) methods, timeline follow-back techniques, or electronic pill cap data, ideal. The outstanding interdisciplinary team for this project includes renowned experts in adherence, graph theory and network analysis, the treatment of HIV, and use of licit and illicit substances. The gamma index offers to provide new insights into underlying patterns of health behavior, their relationship to clinical outcomes, a means of quantifying these patterns, and the possibility of novel real-time interventions to promote healthy behaviors.